HCLAS-X: Hierarchical and Cascaded Lyrics Alignment System Using Multimodal Cross-Correlation

In this work, we address the challenge of lyrics alignment, which involves aligning the lyrics and vocal components of songs. This problem requires the alignment of two distinct modalities, namely text and audio. To overcome this challenge, we propose a model that is trained in a supervised manner, utilizing the cross-correlation matrix of latent representations between vocals and lyrics. Our system is designed in a hierarchical and cascaded manner. It predicts synced time first on a sentence-level and subsequently on a word-level. This design enables the system to process long sequences, as the cross-correlation uses quadratic memory with respect to sequence length. In our experiments, we demonstrate that our proposed system achieves a significant improvement in mean average error, showcasing its robustness in comparison to the previous state-of-the-art model. Additionally, we conduct a qualitative analysis of the system after successfully deploying it in several music streaming services

A Proposal for Foley Sound Synthesis Challenge

"Foley" refers to sound effects that are added to multimedia during post-production to enhance its perceived acoustic properties, e.g., by simulating the sounds of footsteps, ambient environmental sounds, or visible objects on the screen. While foley is traditionally produced by foley artists, there is increasing interest in automatic or machine-assisted techniques building upon recent advances in sound synthesis and generative models. To foster more participation in this growing research area, we propose a challenge for automatic foley synthesis. Through case studies on successful previous challenges in audio and machine learning, we set the goals of the proposed challenge: rigorous, unified, and efficient evaluation of different foley synthesis systems, with an overarching goal of drawing active participation from the research community. We outline the details and design considerations of a foley sound synthesis challenge, including task definition, dataset requirements, and evaluation criteria

Target-Agnostic Gender-Aware Contrastive Learning for Mitigating Bias in Multilingual Machine Translation

Gender bias is a significant issue in machine translation, leading to ongoing research efforts in developing bias mitigation techniques. However, most works focus on debiasing bilingual models without much consideration for multilingual systems. In this paper, we specifically target the gender bias issue of multilingual machine translation models for unambiguous cases where there is a single correct translation, and propose a bias mitigation method based on a novel approach. Specifically, we propose Gender-Aware Contrastive Learning, GACL, which encodes contextual gender information into the representations of non-explicit gender words. Our method is target language-agnostic and is applicable to pre-trained multilingual machine translation models via fine-tuning. Through multilingual evaluation, we show that our approach improves gender accuracy by a wide margin without hampering translation performance. We also observe that incorporated gender information transfers and benefits other target languages regarding gender accuracy. Finally, we demonstrate that our method is applicable and beneficial to models of various sizes.Comment: Accepted to EMNLP 2023 Main Conferenc

Prenatal and Postnatal Factors Regulate Food Intake and Body Composition

This research sought to identify the effects of prenatal and postnatal factors on systemic metabolism and the regulation of food intake, weight, and body composition. It was found that the manipulation of maternal diets influenced the systemic metabolism of offspring. The offspring of dams fed an isocaloric, low protein diet were significantly smaller and consumed less food than offspring from dams fed a control diet. In the case of the offspring from dams fed a western diet, they were significantly heavier and consumed more food than offspring from dams fed a control diet. In addition, the offspring showed altered glucose tolerance and insulin resistance as a function of maternal diets, and effects were observed throughout growth, development, and in response to the modulatory effects of aging and their post-weaning diet. The offspring showed different insulin and leptin concentrations depending on maternal diets, and the altered levels may partially explain differences among groups. Our data indicates that in utero environmental factors program offspring’s metabolism into adulthood, and can contribute to the intergenerational transmission of obesity and cardiometabolic diseases. We hypothesized that DNA methylation occurring prenatally were responsible for altered expression of micro-RNAs (miRNAs), known regulators of gene expression. The absence of miR-150 resulted in increased mTOR protein known to participate in increased leptin production, which leads to reduction of food intake. miR-150 KO mice were found to have an insulin-sensitive phenotype accompanied by changes of gene and protein expression in adipose tissue. Ablation of miR-150 also augmented PGC-1α protein, which subsequently led to expression of genes involved in a futile cycle between fatty acid oxidation and triglyceride synthesis in adipose tissue. However, we found that there was no difference in miR-150 concentration among newborn offspring from dams fed different diets. In summary, we found that the maternal diets and miR-150 are important contributors to regulating systemic metabolism before and after birth, respectively. This data points to potential environmental factors that could be modified during pregnancy to prevent the intergenerational transmission of cardiometabolic disease, and a novel therapeutic target to treat metabolic disease once it is observed in adulthood

Whistleblowing in the Public Sector: A Systematic Literature Review

Public administration scholars have provided a variety of theoretical insights to understand bureaucratic whistleblowing, and have emphasized its ethical, legal, and practical rationales in the context of democratic bureaucracy. To enhance our understanding of this principled dissent behavior in the public sector, this study systematically reviews 71 whistleblowing articles and dissertations that address three aspects in the literature: (1) definitions and theories; (2) methods and data, and (3) factors associated with whistleblowing intention and behavior. The findings show public administration whistleblowing research typically uses Near and Miceli’s definition, grounded on psychology, ethics, and human resource management (HRM) theories. Methodologically, there is a notable recent trend in the growth of empirical research using survey data, and equal attention has been paid to both whistleblowing intention and behavior variables. Based on the review findings, the study discusses two issues—definitional and theoretical—and presents four research agendas for future bureaucratic whistleblowing scholarship.1

Assessing the Impact of the Whistleblower Protection Enhancement Act of 2002: A Quasi-experiment

Is the new shield effective? The impact of the Whistleblower Protection Enhancement Act: A quasi-experimental analysis of U.S. federal government Though the U.S. federal whistleblower protection is designed as a long-term temporal process, and the civil service act has encouraged to federal bureaucrats feel free to make a disclosure for nearly 40 years, the efficacy of the protection is still unclear. In particular, we have a paucity of research using causal methods to determine how the whistleblower protection has shaped the federal workforce over time. This study conducts a quasi-experimental assessment of the impact of the Whistleblower Protection Enhancement Act of 2012 (WPEA) on the Department of Homeland Security bureaucrats’ whistleblowing intention in three distinct ways. First, this study descriptively analyzes federal bureaucrats’ whistleblowing intention from 2010 to 2017 to accumulate general knowledge. Second, it assesses the impact of the WPEA by setting the DHS as a treatment group to test whether the WPEA changed bureaucrats’ willingness to blow the whistle. The use of comparison groups in other federal agencies allows us to consider whether changes in whistleblowing intention are due to the enhancement or a mere reflection of governmentwide trends. Third, it tests whether the findings in business whistleblowing studies are generalizable to the public organization context. The findings indicate that the WPEA has moderate, but statistically significant effects in increasing bureaucrats’ whistleblowing intention. As an implication, this study calls for an academic attention toward “bureaucratic whistleblowing” and theory underlying how to best protect and empower the prospective federal whistleblowers.

Object detection using a single extended feature map

Fully convolutional neural network-based object detectors have achieved considerable detection accuracy in recent years. It is a recent trend to establish complex and deep network architectures for improvement of the detection accuracy. However, object detectors for intelligent vehicle applications require fast inference speed, Iightweight network architecture, and less memory usage as well as high detection accuracy to implement the algorithm in an embedded hardware. In this paper, we propose a fast object detection method based on a single stage and a single extended feature map. A Iightweight network based on an extended paththrough layer is proposed to improve both the accuracy and speed. The extended paththrough layer enlarges the resolution of the last feature map by concatenating later feature maps with lower resolution to earlier feature map maps with higher resolution. The layer helps to search and detect smaller objects more densely on the extended last feature map. Our experimental results show that the proposed detection model outperforms the previous state-of-the-art methods in both detection accuracy and inference speed. © 2018 IEEE

Vertical intra-industry trade and product quality: the case of South Korea, 1996-2003

This paper contributes to empirical research of intra-industry trade, especially vertical intraindustry trade (VIIT), by two aspects. Firstly, we separate VIIT into higher-export-price VIIT and lower-export-price VIIT. Secondly, we give attention to R&D and FDI stock in explaining VIIT determinants. Applied to panel data representing South Korea's bilateral trade with 15 OECD countries and Taiwan from 1996 through 2003, this alternative makes an intricate understanding of the VIIT determinants possible. Main empirical findings are that South Korea's R&D investments focus on price competitiveness while its inward FDI seeks efficiency and its outward FDI seeks a market in this period